Cover Image

Machine learning for data science handbook : data mining and knowledge discovery handbook / Lior Rokach, Oded Maimon, Erez Shmueli, editors.

Show other versions (1)

This book is a major update to the very successful first and second editions (2005 and 2010) of Data Mining and Knowledge Discovery Handbook. Since the last edition, this field has continued to evolve and to gain popularity. Existing methods are constantly being improved and new methods, application...

Full description

Saved in:
Bibliographic Details
Online Access: Full Text (via Skillsoft)
Other Authors: Rokach, Lior (Editor), Maimon, Oded (Editor), Shmueli, Erez (Editor)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, [2023]
Edition:Third edition.
Subjects:
Data mining.
Machine learning.
Data mining
Machine learning
Table of Contents:
  • Introduction to Knowledge Discovery and Data Mining
  • Preprocessing Methods
  • Data Cleansing: A Prelude to Knowledge Discovery
  • Handling Missing Attribute Values
  • Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour
  • Dimension Reduction and Feature Selection
  • Discretization Methods
  • Outlier Detection
  • Supervised Methods
  • Supervised Learning
  • Classification Trees
  • Bayesian Networks
  • Data Mining within a Regression Framework
  • Support Vector Machines
  • Rule Induction
  • Unsupervised Methods
  • A survey of Clustering Algorithms
  • Association Rules
  • Frequent Set Mining
  • Constraint-based Data Mining
  • Link Analysis
  • Soft Computing Methods
  • A Review of Evolutionary Algorithms for Data Mining
  • A Review of Reinforcement Learning Methods
  • Neural Networks For Data Mining
  • Granular Computing and Rough Sets - An Incremental Development
  • Pattern Clustering Using a Swarm Intelligence Approach
  • Using Fuzzy Logic in Data Mining
  • Supporting Methods
  • Statistical Methods for Data Mining
  • Logics for Data Mining
  • Wavelet Methods in Data Mining
  • Fractal Mining - Self Similarity-based Clustering and its Applications
  • Visual Analysis of Sequences Using Fractal Geometry
  • Interestingness Measures - On Determining What Is Interesting
  • Quality Assessment Approaches in Data Mining
  • Data Mining Model Comparison
  • Data Mining Query Languages
  • Advanced Methods
  • Mining Multi-label Data
  • Privacy in Data Mining
  • Meta-Learning - Concepts and Techniques
  • Bias vs Variance Decomposition for Regression and Classification
  • Mining with Rare Cases
  • Data Stream Mining
  • Mining Concept-Drifting Data Streams
  • Mining High-Dimensional Data
  • Text Mining and Information Extraction
  • Spatial Data Mining
  • Spatio-temporal clustering
  • Data Mining for Imbalanced Datasets: An Overview
  • Relational Data Mining
  • Web Mining
  • A Review of Web Document Clustering Approaches
  • Causal Discovery
  • Ensemble Methods in Supervised Learning
  • Data Mining using Decomposition Methods
  • Information Fusion - Methods and Aggregation Operators
  • Parallel and Grid-Based Data Mining Algorithms, Models and Systems for High-Performance KDD
  • Collaborative Data Mining
  • Organizational Data Mining
  • Mining Time Series Data
  • Applications
  • Multimedia Data Mining
  • Data Mining in Medicine
  • Learning Information Patterns in Biological Databases - Stochastic Data Mining
  • Data Mining for Financial Applications
  • Data Mining for Intrusion Detection
  • Data Mining for CRM
  • Data Mining for Target Marketing
  • NHECD - Nano Health and Environmental Commented Database
  • Software
  • Commercial Data Mining Software
  • Weka-A Machine Learning Workbench for Data Mining.

Similar Items